The same plot in 14 other libraries — Python: Altair, Bokeh, lets-plot, Matplotlib, Plotly, plotnine, Pygal, Seaborn; R: ggplot2; JavaScript: Chart.js, D3.js, Apache ECharts, Highcharts, MUI X Charts. Compare all 15 side by side: Basic Scatter Plot in Python, R, Julia and JavaScript.
A fundamental 2D scatter plot that displays the relationship between two numeric variables by plotting points on a Cartesian coordinate system. This visualization is essential for exploring correlations, identifying patterns, detecting outliers, and understanding the distribution of paired data points.
# anyplot.ai
# scatter-basic: Basic Scatter Plot
# Library: makie 0.21.9 | Julia 1.11.9
# Quality: 88/100 | Created: 2026-06-25
using CairoMakie
using Colors
using Random
using Statistics
Random.seed!(42)
# Theme tokens
const THEME = get(ENV, "ANYPLOT_THEME", "light")
const PAGE_BG = THEME == "light" ? colorant"#FAF8F1" : colorant"#1A1A17"
const INK = THEME == "light" ? colorant"#1A1A17" : colorant"#F0EFE8"
const INK_SOFT = THEME == "light" ? colorant"#4A4A44" : colorant"#B8B7B0"
const BRAND = colorant"#009E73"
# Data — adult height (cm) vs weight (kg), simulated health study, n=150
n = 150
height_cm = 170.0 .+ 10.0 .* randn(n)
weight_kg = 0.5 .* height_cm .+ 5.0 .* randn(n) .- 15.0
# Regression line
x_bar = mean(height_cm)
y_bar = mean(weight_kg)
slope = sum((height_cm .- x_bar) .* (weight_kg .- y_bar)) / sum((height_cm .- x_bar) .^ 2)
intercept = y_bar - slope * x_bar
x_fit = LinRange(minimum(height_cm) - 1, maximum(height_cm) + 1, 200)
y_fit = slope .* x_fit .+ intercept
r_val = cor(height_cm, weight_kg)
# Figure
fig = Figure(
size = (1600, 900),
fontsize = 14,
backgroundcolor = PAGE_BG,
)
# Subtitle using Makie compositional layout slot above the main axis
Label(
fig[0, 1],
"Pearson r = $(round(r_val; digits=2)) — positive correlation (height predicts weight, n=$n)",
fontsize = 13,
color = INK_SOFT,
halign = :left,
tellwidth = false,
)
ax = Axis(
fig[1, 1];
title = "scatter-basic · julia · makie · anyplot.ai",
titlesize = 23,
titlecolor = INK,
xlabel = "Height (cm)",
ylabel = "Weight (kg)",
xlabelsize = 14,
ylabelsize = 14,
xlabelcolor = INK,
ylabelcolor = INK,
xticklabelsize = 12,
yticklabelsize = 12,
xticklabelcolor = INK_SOFT,
yticklabelcolor = INK_SOFT,
xticksvisible = false,
yticksvisible = false,
backgroundcolor = PAGE_BG,
topspinevisible = false,
rightspinevisible = false,
leftspinecolor = INK_SOFT,
bottomspinecolor = INK_SOFT,
xgridcolor = RGBAf(INK.r, INK.g, INK.b, 0.15),
ygridcolor = RGBAf(INK.r, INK.g, INK.b, 0.15),
)
scatter!(
ax, height_cm, weight_kg;
color = (BRAND, 0.7),
markersize = 12,
strokewidth = 1,
strokecolor = PAGE_BG,
)
lines!(ax, collect(x_fit), collect(y_fit); color = INK_SOFT, linewidth = 2.0, linestyle = :dash)
# Save
save("plot-$(THEME).png", fig; px_per_unit = 2)
Runnable source as JSON, for any HTTP client: https://api.anyplot.ai/specs/scatter-basic/makie/code. Any spec id and library id listed in llms-full.txt fit the same URL shape; every URL below is complete and callable.
{
"spec_id": "scatter-basic",
"language": "julia",
"library": "makie",
"page": "https://anyplot.ai/scatter-basic/julia/makie",
"hub": "https://anyplot.ai/scatter-basic",
"code_json": "https://api.anyplot.ai/specs/scatter-basic/makie/code",
"spec_json": "https://api.anyplot.ai/specs/scatter-basic",
"render_light_png": "https://storage.googleapis.com/anyplot-images/plots/scatter-basic/julia/makie/plot-light.png",
"render_dark_png": "https://storage.googleapis.com/anyplot-images/plots/scatter-basic/julia/makie/plot-dark.png",
"quality_score": 88.0,
"license": "MIT",
"guide": "https://anyplot.ai/llms.txt"
}Part of Basic Scatter Plot on anyplot.ai.